Nikiforov Igor

Igor NIKIFOROV is a professor at the University of Technology of Troyes, Troyes, UTT/STMR/LM2S, UMR CNRS 6281, France. He received the M.S. degree from the Moscow Physical - Technical Institute in 1974 and the Ph.D. from the Institute of Control Sciences, Moscow (Academy of Science), in 1981. He spent 1974-1992 at the Institute of Control Sciences, Academy of Science, Moscow. He spent 1992 – 1995 as senior researcher at the IRISA/INRIA, Rennes, and at the University of Science and Technology of Lille 1, France. From 1995 to now he is with the University of Technology of Troyes. Igor Nikiforov is currently active or has demonstrated activity in the past in the following areas: sequential change detection and isolation, multiple hypotheses case, statistical signal detection with nuisance parameters, navigation system integrity monitoring, safety critical system monitoring, network anomaly detection, tomography, cyber-criminalistics. Administrative positions: 2000 – 2007: responsible for the systems modeling and dependability laboratory (LM2S) of the Charles Delaunay Institute, FRE CNRS 2848. 2004 – 2005: director of the Institute of Sciences and Technology of Information of Troyes (ISTIT, FRE CNRS 2732)


«Navigation and information technologies for efficient state and municipal management»
«Statistical model of local noise/multipath effects for integrity monitoring in the urban environment»
For many safety-critical applications, a serious problem of the existing global navigation satellite systems (GNSS)
consists in their lack of integrity. Two different integrity monitoring approaches can be defined for ground transportation
systems : “the passive integrity” and “the active integrity”. The passive integrity allows all measurements
without rejection and simply lengthens the protection zone (i.e. the alert limit). This method assures that the local
noise/multipath effects, GNSS signal attenuation and corruption (with bounded impacts on the vehicle position) will
not cause unsafe positioning. The active integrity method or RAIM includes two functions : the detection of a position
failure and the exclusion of the contaminated pseudorange(s) from the GNSS navigation solution. For both
integrity approaches (passive and active), an important element of the GNSS statistical description is the model of
local noise/multipath effects, which can be dominant in the urban environment. With other models (tropospheric, ionospheric,
etc.), the local model provides us with a formalized definition of precision and integrity levels of 1D (train)
and 2D (surface vehicle) positioning.
The local noise/multipath effects model is considered as a nonlinear parametric model of the heteroscedasticity.
The heteroscedasticity occurs in regression when the measurement noise variance is non-constant. In our case, the
noise variance can be represented as a parameterized function (so-called variance function) of independent variables
(the satellite elevation angle at each GNSS epoch and the signal-to-noise ratio C/N0 at the same GNSS epoch). The
maximum likelihood estimation (MLE) of variance function parameters leads to a system of nonlinear equations. The
iterative solution of these nonlinear equations is based entirely on a successful choice of initial conditions. Hence,
in the practice, the nonlinear MLE is intractable. To overcome this difficulty, another linear quasi-MLE estimator is
proposed. It is strongly consistent, asymptotically Gaussian and only slightly less efficient than the Cramer-Rao lower
bound.By using this estimator as an initial condition, an asymptotically efficient estimation of the local noise/multipath
effects model is obtained by using one-step non-iterative Newton method.
Acknowledgments. The author gratefully acknowledge partial research and financial support of this work from the
Centre National d’Etudes Spatiales (CNES), France, Thales Alenia Space, France and M3 Systems, Toulouse, France.